Stream flow prediction using TIGGE ensemble precipitation forecast data for Sabarmati river basin

Flooding is the most prevalent natural disaster globally. Increasing flood frequency affects developing nations as these countries lack strong forecasting systems. The most flood-prone urban regions are near the coast or riverbanks. Using The International Grand Global Ensemble (TIGGE) data, a coupled atmospheric-hydrologic ensemble flood forecasting model for the Sabarmati river was developed. Incorporating numerical weather prediction (NWP) information into flood forecasting systems can increase lead times from hours to days. When predicting the weather, we employed numerous NWP models from... Mehr ...